The accelerating growth of solar photovoltaic (PV) interconnections is expected to be an important component of an overall global strategy to reduce greenhouse gas emissions from the building sector. The penetration of rooftop solar has been growing quickly in many parts of the United States, most notably in California. For example, over 25% of the United States rooftop solar installations are in California, with some major utility companies servicing over 260,000 customers with rooftop solar, while connecting about 6,000 new customers per month. The penetration of solar is expected to continue growing due to various policy initiatives, decreasing solar costs, new leasing models or purchases without upfront costs, and natural turnover of housing stock (including remodeled and new housing).
The rapid growth of solar photovoltaic interconnections has posed challenges to the management of the distribution system. With rooftop solar becoming more prevalent, it is quickly becoming an important source of electric generation for many power distribution providers. As with any generation asset, the reliable prediction of generation profiles is essential for forecasting and planning purposes, particularly since typical rooftop solar cannot currently be dispatched. This need becomes even more pronounced at geographically granular levels, where distributed generation has significant implications for distribution systems in terms of operations and planning.
Further, there are also some implications for customers who use unauthorized solar photovoltaic systems, for those customers with authorized solar photovoltaic systems, and those without solar photovoltaic systems. For example, customers without permission to operate their solar photovoltaic systems are unable to sign up for advantageous net energy metering (hereinafter “NEM”) rates. Moreover, customers considering installation of solar photovoltaic in the future may not fully factor into their investment decision future rate structures intended to guide value-based location of distributed solar photovoltaic. In the long run, solar customers with unauthorized connections may bypass distribution charges, unfairly placing those costs onto other customers. Distribution costs are not driven by the amount of kWh consumed, but by utilization of the distribution grid. The construct of recovering distribution costs based on energy consumption charges (kWh) is a holdover from a time when energy consumption could only be measured on a monthly basis. Over time, rates are expected to evolve to better align with the actual drivers of distribution system costs.
Without accurate solar photovoltaic location data, a utility is unable to accurately plan system upgrades based on the load and amount of distributed generation behind that equipment. As an example, engineering calculations determine when a secondary transformer or other equipment should be upgraded based on the amount of interconnected solar behind that equipment. Underestimation of the actual amount of solar due to unreported or inaccurately reported interconnections, can lead to voltage problems or other reliability issues. Customers who have not received interconnection authorization may have bypassed important building code requirements when installing their solar photovoltaic system.
A recent literature review of potential safety issues associated with unauthorized interconnections found that, while a small risk exists for utility workers who are servicing circuits with unidentified solar photovoltaic systems present as well as other risks, the most tangible risk from unauthorized interconnections are present on the customer side of the meter. Excessively high penetration rates of solar photovoltaic on feeders that are not rated for it may experience voltage fluctuations that could compromise service reliability.
A more up to date and accurate source of distributed solar photovoltaic system location data would better inform efforts to capture locational value of distributed solar photovoltaic and plan for hosting capacity while understanding system impacts and minimizing costs. Fortunately, because solar photovoltaic systems produce electricity and impact net household loads with reasonably regular patterns, meter load data (e.g., from so-called smart meters) is a readily available, a rich source of information that can be used to improve upon current interconnection database information. By combining load data, weather patterns, customer locations, and interconnection data, it is possible to identify patterns which are consistent with interconnected solar photovoltaic systems. This pattern matching can be used to predict whether a particular location has an interconnected solar photovoltaic system. Locations which exhibit patterns consistent with solar photovoltaic systems but which do not appear in the interconnection database or mismatch between the size of solar photovoltaic reported in the interconnection database and the predicted size of the solar photovoltaic systems can be flagged.